DOI: https://doi.org/10.14710/medstat.14.1.33-43

ROBUST PORTFOLIO SELECTION WITH CLUSTERING BASED ON BUSINESS SECTOR OF STOCKS

*La Gubu orcid scopus  -  Jurusan Matematika, FMIPA, Universitas Halu Oleo, Indonesia
Dedi Rosadi  -  Departemen Matematika, FMIPA, Universitas Gadjah Mada, Indonesia
Abdurakhman Abdurakhman  -  Departemen Matematika, FMIPA, Universitas Gadjah Mada, Indonesia
Open Access Copyright (c) 2021 MEDIA STATISTIKA under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract
In recent years there have been numerous studies on portfolio selection using cluster analysis in conjunction with Markowitz model which used mean vectors and covariance matrix that are estimated from a highly volatile data. This study presents a more robust way of portfolio selection where stocks are grouped into clusters based on business sector of stocks. A representative from each cluster is selected from each cluster using Sharpe ratio to construct a portfolio and then optimized using robust FCMD and S-estimation. Calculation Sharpe ratio showed that this method works efficiently on large number of data while also robust against outlier in comparison to k-mean clustering. Implementation of this method on stocks listed on the Indonesia Stock Exchange, which included in the LQ-45 indexed for the period of August 2017 to July 2018 showed that portfolio performance obtained using clustering base on business sector of stocks combine with robust FMCD estimation is outperformed the other possible combination of the methods.
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Keywords: business sector; portfolio; Sharpe ratio; robust estimation; portfolio performance
Funding: Universitas Gadjah Mada

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Language : EN
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  1. Best, M. J., & Grauer, R. R. (1991). On the Sensitivity of Mean-Variance-Efficient Portfolios to Changes in Asset Means: Some Analytical and Computational Results. Review of Financial Studies, 4(2), 315–342. https://doi.org/10.1093/rfs/4.2.315
  2. Ceria, S., & Stubbs, R. A. (2006). Incorporating estimation errors into portfolio selection: Robust portfolio construction. Journal of Asset Management, 7(2), 109–127. https://doi.org/10.1007/978-3-319-30794-7_12
  3. Chen, L. H., & Huang, L. (2009). Portfolio optimization of equity mutual funds with fuzzy return rates and risks. Expert Systems with Applications, 36(2 PART 2), 3720–3727. https://doi.org/10.1016/j.eswa.2008.02.027
  4. Chopra, V. K., & Ziemba, W. T. (1993). The effect of errors in means, variances, and covariances on optimal portfolio choice. Journal of Portfolio Management, 19(2), 6–11. https://doi.org/10.1142/9789813144385_0002
  5. Davies, P. L. (1987). Asymptotic Behaviour of S-Estimates of Multivariate Location Parameters and Dispersion Matrices. The Annals of Statistics, 15(3), 1269–1292. https://doi.org/10.1214/aos/1176350505
  6. DeMiguel, V., & Nogales, F. J. (2009). Portfolio selection with robust estimation. Operations Research, 57(3), 560–577. https://doi.org/10.1287/opre.1080.0566
  7. Fabozzi, F. J., Kolm, P. N., Pachamanova, D. A., & Focardi, S. M. (2007). Robust portfolio optimization. John Wiley and Sons, Inc
  8. Guan, H. S., & Jiang, Q. S. (2007). Cluster financial time series for portfolio. Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR ’07, 2, 851–856. https://doi.org/10.1109/ICWAPR.2007.4420788
  9. Gubu, L., Rosadi, D., & Abdurakhman. (2020). Robust mean-variance portfolio selection with ward and complete linkage clustering algorithm. Economic Computation and Economic Cybernetics Studies and Research, 54(3), 111–127. https://doi.org/10.24818/18423264/54.3.20.07 117
  10. Hardin, J. S. (2000). Multivariate outlier detection and robust clustering with minimum covariance determinant estimation and S-estimation. Ph.D. Dissertation University of California
  11. Lauprete, G. J. (2001). Portfolio risk minimization under departures from normality. Ph.D. Dissertation Massachusetts Institue of Technology
  12. Long, N. C., Wisitpongphan, N., Meesad, P., & Unger, H. (2014). Clustering stock data for multi-objective portfolio optimization. International Journal of Computational Intelligence and Applications, 13(2), 1–13. https://doi.org/10.1142/S1469026814500114
  13. Lopuhaa, H. P. (1989). On the Relation between S-Estimators and M-Estimators of Multivariate Location and Covariance. The Annals of Statistics, 17(4), 1662–1683
  14. Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77–91. https://doi.org/10.1111/j.1540-6261.1952.tb01525.x
  15. Maronna, R. A., Martin, R. D., & Yohai, V. J. (2006). Robust Statistics: Theory and Methods. In Robust Statistics: Theory and Methods. John Wiley & Sons, Ltd
  16. Nanda, S. R., Mahanty, B., & Tiwari, M. K. (2010). Clustering indian stock market data for portfolio management. Expert Systems with Applications, 37(12), 8793–8798. https://doi.org/10.1016/j.eswa.2010.06.026
  17. Rifa, I. H., Pratiwi, H., & Respatiwulan, R. (2020). Clustering of Earthquake Risk in Indonesia Using K-Medoids and K-Means Algorithms. Media Statistika, 13(2), 194–205. https://doi.org/10.14710/medstat.13.2.194-205
  18. Rousseeuw, P. J., & Van Driessen, K. (1999). Fast Algorithm For Minimum Covariance Determinant Estimator. Technometrics, 41(3), 212–223
  19. Rousseeuw, P., & Yohai, V. (1984). Robust Regression By Means of S estimators. Lecture Notes in Statistics: Robust and Nonlinear Time Series Analysis, 26, 256–272
  20. Sharpe, W. F. (1994). The Sharpe Ratio. The Jornal of Portfolio Management, 21, 49–58
  21. Supandi, E. D. (2017). Developing of Mean-Variance Portfolio Modeling Using Robust Estimastin and Robust Optimization Method. Ph.D. Dissertation Gadjah Mada University
  22. Tola, V., Lillo, F., Gallegati, M., & Mantegna, R. N. (2008). Cluster analysis for portfolio optimization. Journal of Economic Dynamics and Control, 32(1), 235–258. https://doi.org/10.1016/j.jedc.2007.01.034
  23. Vaz-de Melo, B., & Camara, R. P. (2005). Robust multivariate modeling in finance. International Journal of Managerial Finance, 1(2), 95–107. https://doi.org/10.1108/17439130510600811
  24. Welsch, R., & Zhou, X. (2007). Application of robust statistics to asset allocation models. REVSTAT–Statistical Journal, 5(1), 97–114
  25. Winston, W. L., & Goldberg, J. B. (2004). Operations research. In Operations Research: Applications and Algorithms (4th ed.). Thomson Learning Inc
  26. Würtz, D., Chalabi, Y., Chen, W., & Ellis, A. (2009). Portfolio Optimization with R / Rmetrics. 419. https://finance.e-bookshelf.ch/portfolio-optimization-with-r-rmetrics-2329769.html

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